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OPTIKO

Optimization of cauliflower cultivation by monitoring with UAVs and machine-learning

Runtime
01.01.20 - 31.12.22

In the project OPTIKO, we will use unmanned aerial vehicles (UAVs) to monitor growth and performance of cauliflower. By combining multispectral images taken by UAV-based low cost multispectral cameras with a machine learning algorithms for data analysis, we will develop an innovative process to assess traits of individual cauliflower plants. Machine learning algorithms will be trained to detect heterogeneities within a field based on spectral and spatial information, which indicate reduced plant performance due to abiotic and biotic stress. In the future, automatized, regular UAV overflights could be used for the early detection of stress symptoms and precise application of respective management procedures, such as fertilization or the application of pesticides. In addition, multispectral data will be used to predict the date of harvest, which will allow for an improved managing of sales and thus stabilize the sales benefits. By the development of this novel process, which will be transferable to further crops in the future, OPTIKO contributes to the digitalization of agriculture and complement already established operational processes and existing agro-machinery technology.

The project is funded by the Ministerium für Klimaschutz, Umwelt, Landwirtschaft, Natur- und Verbraucherschutz des Landes Nordrhein-Westfalen in the framework of the European Innovation Partnership 'Agricultural Productivity and Sustainability'

Funded by

Europäischer Landwirtschaftsfonds für die Entwicklung des ländlichen Raums:
Hier investiert Europa in die ländlichen Gebiete unter Beteiligung des Landes Nordrhein-Westfalen

Funded by




Consortium

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